Plant material and sampling strategy

From June 2008 to December 2010, we sampled 400 individuals of A. schaueriana from 11 localities and 181 individuals of A. germinans from seven locales along the Brazilian coast, covering more than 4900 km of coastline, to evaluate local (thousands of meters, microscale), regional (hundreds of kilometers, mesoscale) and continental geographic scales (thousands of kilometers, macroscale) (Fig. 1, Table 1). Latitude and longitude were recorded using a global positioning system (Garmin 76CSx, WGS-84 standard, Garmin International Inc., Olathe, KS, USA). Licenses (17159 and 17130) to collect the leaves and reproductive branches of these species were obtained from the Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA, currently, Instituto Chico Mendes de Conservação da Biodiversidade, ICMBio).

Each species sample is presented in Table 1, with Ag and As indicating A. germinans and A. schaueriana, respectively; localities from which the samples were obtained are indicated with three letter abbreviations. For A. germinans, we collected individuals from two nearby localities in Bragança, Pará, Brazil that experience different tidal influences: one area in which inundation frequency was reduced due to changes in the hydrographic regime caused by highway construction (AgPAa) [19], and another that experienced a regular tidal pattern (AgPAb) (Fig. 1, Table 1). To minimize misidentification, we distinguished species in the field based on both vegetative and reproductive traits. We identified A. germinans individuals by their ovate leaves that usually present a blunt apex; by their long, exserted stamens; and by their conspicuously hairy petals. We identified A. schaueriana by their obovate leaves; by their inserted stamens; and by their glabrous inner-face corolla [1]. Voucher specimens from every location, except for the AsALC and AgALC samples, were deposited and cataloged in the University of Campinas (UEC) and Embrapa Amazônia Oriental (IAN) herbaria, both of which are located in Brazil. We sampled leaves from flowering trees located at least 20 m from any other tree, and leaves were stored in zip-lock bags containing silica gel. Leaf material was lyophilized and stored at −20°C prior to DNA isolation. Despite our best sampling efforts, we found few individuals (five) of A. germinans presenting flowers at AgPRC (Table 1).

In June 2008, we randomly chose 24 mother trees separated by at least 30 m from AsAJU for the A. schaueriana mating system analyses (Fig. 1, Table 1). In total, 288 healthy propagules attached to the tree were sampled from each of these trees, with a mean of 12 propagules per parental plant (ranging from 8 to 14). Each progeny was stored in an individual zip-lock bag in the field, and when brought to the laboratory, each fruit was stored in distilled water to isolate the pericarp from the embryo, which was stored at −80°C until DNA extraction.

A. schaueriana microsatellite development and molecular biology procedures

For total genomic DNA isolation, we ground leaf samples and whole embryos into fine powder in liquid nitrogen, according to a cetyltrimethyl ammonium bromide protocol. The genetic diversity of each Avicennia species was analyzed using previously published microsatellite markers for A. germinans [22–24] and markers developed for A. schaueriana (described herein), which were isolated to achieve more reliable results using a larger number of loci for both species. The A. schaueriana microsatellites were developed using a method previously used to isolate A. germinans markers [24]. Monomorphic markers for A. germinans [24] were tested using a subsample of eight individuals from three and five locales for A. germinans and A. schaueriana, respectively. Markers showing intra- or interspecific polymorphisms were considered in subsequent examinations (Table 2).

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Table 2. Microsatellites markers used in this study.

https://doi.org/10.1371/journal.pone.0118710.t002

Polymerase chain reactions (PCRs) were performed as previously described [24] or with certain modifications [22, 23] (Table 2). Amplification products were visualized via vertical electrophoresis in 1× TBE, 6% polyacrylamide denaturing gels stained with silver nitrate. Product sizes were determined by comparison to a 10 bp DNA ladder (Invitrogen, Carlsbad, CA, USA). Approximately 10% of the total samples were re-genotyped to evaluate scoring genotyping errors. To evaluate the A. schaueriana mating systems, only markers that presented polymorphisms at AsSAL, AsAJU and AsPRM were employed, except for the loci Agerm6 and Agerm8, out of a total of 13 markers.

Intraspecific genetic diversity analyses

After characterizing the A. schaueriana markers, we tested the occurrence of linkage disequilibrium (LD) for all pairs of markers per sample using the FSTAT 2.9.3 software program [25]. As we found consistent evidence of LD for A. germinans and A. schaueriana, we considered 22 and 17 polymorphic markers for further analyses, respectively (Table 2).

Using the MICRO-CHECKER software program [26], we observed evidence of null alleles and stuttering (Table 2). However, despite these indications, we observed no substantial differences between the global and pairwise G_ST values of samples that were corrected or not corrected for null alleles using the “excluding null alleles” method implemented in the FreeNA software [27] (S1 and S2 Tables); therefore, we used the original dataset for further analyses. We evaluated intraspecific genetic variation based on the average effective number of alleles (N_e), the expected (H_E) and observed heterozygosities (H_O), and the fixation index (f) for each sample using GenAlEx 6.5 software [28]. The apparent outcrossing rate (t_a) was determined as (1 - f)/(1 + f) assuming Wright equilibrium [29] (Table 3). We tested each sample for Hardy-Weinberg equilibrium (HWE) using heterozygote deficiency as the alternative hypothesis in the Genepop 4.0 software program [30].

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Table 3. Intraspecific genetic diversity of A. germinans and A. schaueriana samples from the Brazilian coast.

Sample codes are denoted as in Table 1.

https://doi.org/10.1371/journal.pone.0118710.t003

Population structure within species

Considering the different sets of microsatellite markers for each species, we used different approaches to evaluate how genetic diversity within each species is organized. We assessed population structure using the summary statistics D [31] and G_ST [32] using the diveRsity package [33]. The reliability of these statistics was verified using 10⁵ permutations. We also verified the pairwise relations of these statistics between every pair of localities, and we evaluated isolation by distance (IBD) by performing a Mantel test in the ade4 software program [34], considering the approximate linear distance between the sample locales along the coastline and the summary statistics G_ST [32] and D [31]. The Mantel correlograms were calculated in the vegan package [35], considering 10 classes of geographic distances for A. germinans and 15 for A. schaueriana, with 10⁵ permutations performed to verify the significant correlations.

To further analyze how genetic diversity is structured within each species, we used a multivariate method known as discriminant analysis of principal components (DAPC) [36] implemented in the R package ADEGENET 1.3.7 [37], considering the samples from each locale as different groups. We applied this model-free approach, which provides principal components (PCs) that rely solely on the inter-population variability [36], and we retained seven and six PCs that represented 49.9% and 60.4% of the total genetic information of A. germinans and A. schaueriana samples, respectively, with the number of clusters (k) varying from 1 to 50. The number of PCs was chosen using the optim.a.score function to avoid over-fitting during discrimination. The choice of an optimal k value was based on the Bayesian information criterion provided for each k tested. We also used the model-based clustering method implemented in the Structure 2.3.4 software program, assuming correlated allele frequencies and admixture [38,39], and disregarding any a priori information. We performed 50 independent Markov chain Monte Carlo (MCMC) runs for each k, which ranged from 1 to 10 for A. germinans and from 1 to 15 for A. schaueriana, with 5×10⁵ iterations following a burn-in period of 5×10⁵ iterations. The k value that best explained our data was determined using both maximization of the logarithm likelihood of the data, lnL [38], and the ad hoc statistic ΔK [40]. We used the CLUMPP software [41] to address label switching and multimodality issues using the Greedy algorithm, with 10⁶ random input orders. For A. schaueriana, to determine fine-scale population structure revealed throughout the analyses, we used the same strategy described above for each of the two clusters we obtained (see below), with k ranging from 1 to 10 for each group. We used an extended model-based approach implemented in the InStruct software [42] to consider inbreeding—which is likely to be a violated condition in these species (see below)—without prior information regarding spatial location or sample membership. We performed five independent runs of 10⁶ MCMC repetitions with a 5×10⁵ burn-in period for each. We also performed hierarchical analyses of molecular variance (AMOVA) using permutation procedures (10⁵ iterations) in the Arlequin 3.5 program [43], considering the clusters identified using both multivariate and Bayesian methods. For this purpose, we considered the F_ST analog estimator under the infinite alleles mutation model (IAM) [44].

Ongoing hybridization between A. germinans and A. schaueriana

To evaluate the ongoing hybridization between these Avicennia species, we used a different set of markers as only microsatellites that yielded PCR products for both species were considered to reduce marker development bias. We evaluated 20 microsatellites in these analyses, including intraspecific monomorphic markers that showed variation between species (Table 2).

The same methods used to study genetic diversity and population structure described above, with the exception of InStruct, were used in this investigation. For DAPC analysis, we used seven PCs, which explained 67.7% of the variance using every species sample as a priori clusters. In addition to using the same model-based clustering approach described above [38,39], with k ranging from 1 to 10, we arbitrarily defined a threshold of 0.15 for membership probability to assess any sign of historical hybridization. We also evaluated the existence and categories (F₁, F₂ and backcrosses between a “pure species” and a F₁) of eventual two-generation hybrids between each “pure species,” employing a different model-based method implemented in the NewHybrids 1.1 beta software [45]. For this purpose, we evaluated the posterior distributions using five independent chains of 10⁶ MCMC following 5×10⁵ burn-in steps without prior allele frequency information, considering Jeffrey-type and uniform distribution priors for θ and π. We also evaluated the groups identified with these approaches using hierarchical AMOVA to evaluate how genetic diversity is organized between and within A. germinans and A. schaueriana.

A. schaueriana mating system

Using 24 open-pollinated progeny arrays composed of 288 individuals, we evaluated the mating system of A. schaueriana under the mixed mating model for unlinked markers [46] using the program MLTR v3.4 [47]. According to this method, considering both Newton-Raphson (NR) and expectation-maximization (EM) methods regarding the absence and presence of null alleles, we estimated the multilocus (t_m) and single-locus (t_s) outcrossing rates, the outcrossing rate between related individuals (t_m-t_s), the average single locus inbreeding coefficient of maternal parents (F_m) and the multilocus paternity correlation (r_p(m)). Standard error was determined based on 10⁴ bootstraps among families.

A. schaueriana microsatellite development and intraspecific genetic diversity

Of the 192 sequenced clones that constituted the constructed library, 52 presented 60 microsatellites. Based on these loci, we designed 43 primer pairs, 16 of which were excluded from further analyses due to amplification failure, unexpected fragment size or nonspecific products. Of the remaining markers, 18 were monomorphic for A. germinans and A. schaueriana, eight were polymorphic for A. germinans, and nine were informative for A. schaueriana (Table 2).

We observed varying degrees of polymorphism among markers within and between samples of each species in terms of N_e, H_E and H_O (Table 3). We measured significant departures from HWE for every sample of both species. We also observed f values ranging from 0.112 to 0.481 for A. schaueriana and from −0.002 to 0.662 for A. germinans, with average values of 0.242 and 0.174, respectively. Therefore, there was evidence that these species exhibit mixed mating systems as the average t_a estimated for the former was 0.610 and 0.704 for the latter (Table 3).

A. schaueriana mating system

Regardless of the method used (NR or EM, with or without considering the presence of null alleles), the results were similar and differed only when thousandths were considered; therefore, only the EM results disregarding null allele outcomes are shown. We observed a predominantly outcrossing mixed-mating system (t_m = 0.542 ± 0.062, t_s = 0.232 ± 0.065) for this progeny array, which was in accordance with the t_a (0.529) estimated for AsAJU, which was composed of only reproductive individuals, with F_m = 0.232 ± 0.065 assuming Wright’s equilibrium. We also observed that biparental inbreeding (t_m—t_s = 0.151 ± 0.026) contributed to the apparent selfing rate of the progeny, which showed a fraction composed of full-sibs (r_p(m) = 0.178 ± 0.057).

Population structure within species

We found substantial evidence for differentiation among the samples with global G_ST and D values of 0.241 and 0.263 for A. germinans and 0.480 and 0.127 for A. schaueriana, respectively. The pairwise G_ST and D values for both species were highly correlated, indicating a varying degree of differentiation among different pairs of samples for both species (rho ≥ 9.11 for all cases, Fig. 2 and S3 Table), despite the lower values of D than G_ST for A. schaueriana. These results indicate that substantial genetic structure exists for both species, primarily when samples north and south of the northeastern extremity of South America (NEESA—Fig. 1) are considered (Fig. 2, S1 and S2 Figs.). For simplicity, we use “Ag” and “As” as acronyms for A. germinans and A. schaueriana, respectively, and “N” or “S” as codes for samples north and south of the NEESA, respectively.

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Fig 2. Pairwise comparisons of population genetic differentiation in A. germinans and A. schaueriana.

Pairwise measurements of the genetic variation between samples in terms of Nei’s G_ST (1973—below diagonal) and D (Jost 2008—above diagonal) values in A) both A. germinans and A. schaueriana, B) A. germinans, and C) A. schaueriana samples. AgN and AgS and AsN and AsS refer to samples of A. germinans and A. schaueriana taken from locales north and south of the NEESA, respectively. All measures were significant (p < 0.05).

https://doi.org/10.1371/journal.pone.0118710.g002

A significant association was found between genetic and geographic distances, as indicated by the D and G_ST values for A. germinans and A. schaueriana (p < 0.01 for both species, with r_M = 0.777 and r_M = 0.696 for the former considering G_ST and D, and r_M = 0.755 and r_M = 0.830 for the latter). The observed IBD was even more evident when we evaluated the correlograms of r_M and classes of geographic distance (Fig. 3), which indicate a significant positive spatial structure. This IBD pattern was particularly evident when the multivariate DAPC analyses were considered. Using this method, we found that k was equal to 4 for A. germinans, with a substantial differentiation between TMD and the remaining samples (Fig. 4A). Also considering the DAPC analyses, for A. schaueriana, the most likely inferred k value was 10, and similarly, a clear pattern of divergence was observed between AsN and AsS (Fig. 5A).

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Fig 3. Isolation by distance of A. germinans and A. schaueriana.

Mantel correlograms performed on approximated distances between each pair of sample locales along the coastline for A) A. germinans and B) A. schaueriana. Black interconnected circles refer to D [31], and gray interconnected squares indicate Nei’s genetic distance [69]. Filled squares and circles indicate significant correlations (p < 0.05) after 10,000 permutations.

https://doi.org/10.1371/journal.pone.0118710.g003

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Fig 4. A. germinans population structure along the Brazilian coast.

A) A scatterplot of the first two principal components of the multivariate analysis of DAPC [36], which resulted in a most likely k value of 4. Symbols indicate the group to which each individual was assigned. The geographic origin of each individual is denoted for each locality sample such that more than 10% of the total number of individuals was composed of the inferred cluster. A larger symbol indicates that a cluster was predominant in the locality sample (pairwise cluster ratio larger than 1:5), whereas equal symbol sizes indicate similar cluster contributions to the total number of individuals in each sample. B1) Model-based clustering analyses [38,39] considering k = 2 and B2) k = 8, where each individual is represented by a vertical line and each color refers to one inferred cluster; the posterior probability of group membership is indicated.

https://doi.org/10.1371/journal.pone.0118710.g004

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Fig 5. A. schaueriana population structure along the Brazilian coast.

A) A scatterplot of the first two principal components of the multivariate analysis of DAPC [36], which resulted in a most likely k value of 10. Each symbol indicates the group to which each individual was assigned. The geographic origin of each individual is denoted for each locality sample such that more than 10% of the total number of individuals was composed of the inferred cluster. A larger symbol indicates that a cluster was predominant in the locality sample (pairwise cluster ratio larger than 1:5), whereas equal symbol sizes indicate similar cluster contributions to the total number of individuals in each sample. B1) Model-based clustering analyses [38,39] considering k = 2, where each individual is represented by a vertical line and each color refers to one inferred cluster; the posterior probability of group membership is indicated. These Bayesian analyses were extended to the inferred groups observed in B1, which correspond to samples north (green) and south (violet) of the NEESA. The posterior probabilities of group membership in this fine-scale analysis of AsN (k = 4) and AsS (k = 2) are shown in B2; further evaluations of AsS (k = 6) are displayed in B3.

https://doi.org/10.1371/journal.pone.0118710.g005

Using the model-based method implemented in the Structure software, we observed two possible scenarios for A. germinans: k = 2 (AgN and AgS), as the most likely number of populations according to the ΔK approach, and k = 8, as an alternative scenario of finer genetic structure based on lnL and a smaller ΔK value peak (Fig. 6B). These results indicate the existence of a multiple-scale genetic structure. The fine-scale scenario suggests the divergence of samples across every evaluated sampling site, including AgPAa and AgPAb, which are separated by thousands of meters. For A. schaueriana, the most likely k value was 2 (AsN and AsS), based only on ΔK (Fig. 6C). Each of these groups was evaluated separately based on the pairwise G_ST, D (Fig. 2), and DAPC (Fig. 5A) results. Finer-scale genetic structure was evident with AsN presenting k = 4 based on the ΔK values; with AsS presenting k = 2 based on the ΔK value; and with AsS showing k = 6 based on lnL and a smaller ΔK value peak (Fig. 6D and 6E). When inbreeding was considered, similar patterns of genetic structure were observed (S3 and S4 Figs.), despite the different inferred k values for both species (10 for A. germinans and 11 for A. schaueriana). Therefore, both species clearly exhibit variations in genetic structure on different geographic scales, which is in partial agreement with the IBD results as we found two inferred groups (AgPAa and AgPAb) that were clearly distinguished at the genetic level despite their geographic proximity. In all cases, a correspondence was observed between samples from each locality and the inferred clusters, which also allowed for the inference of admixed individuals and migrants (Figs. 4, 5, S1 and S2 Figs.).

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Fig 6. Bayesian inference of cluster number (k).

The mean values of log posterior probability of data (lnL—isolated gray circles, left-axis [38]) and the ΔK ad hoc statistic (interconnected squares, right axis [40]) considering A) samples of both A. germinans and A. schaueriana, B) samples of A. germinans, C) individuals of A. schaueriana from all locales sampled, D) individuals of A. schaueriana from the northern cluster (AsN), and E) samples of A. schaueriana from the southern cluster (AsS).

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The results of the hierarchical AMOVA indicated that the variation was primarily between AsN and AsS (45.88%). For this species, the among-group fixation indexes were significant, although they were lower in terms of the proportion of variation (Table 4) when fine-scale scenarios were considered (k = 4 for AsN and k = 5 or 8 for AsS). With respect to A. germinans, the variation between AgN and AgS, although substantial, was not supported by the permutation tests. However, when all seven samples were considered, a significant and substantial proportion of the variation could be explained by this level of the hierarchy (15.37%) (Table 4).

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Table 4. Analysis of molecular variance (AMOVA) for A. germinans and A. schaueriana samples.

https://doi.org/10.1371/journal.pone.0118710.t004

Ongoing hybridization between A. germinans and A. schaueriana

We observed that as expected, the observed differentiation between species was greater than the differentiation among samples within each species, with global G_ST and D values of 0.583 and 0.549, respectively, which were considerably higher than the values observed for individual species. Pairwise comparisons between samples, both within and between species, also indicated that the interspecific differences were much more pronounced than the intraspecific differences (Fig. 2). These results were also consistent with the hierarchical AMOVA approach, which revealed that the majority of the variation (58.92%) could be explained between species, although considerable and significant genetic variation remained between populations within each species (17.6%) (Table 4).

Regarding the DAPC results, we observed an optimum of 11 clusters, revealing the differences between A. germinans and A. schaueriana (Fig. 7A). The patterns of genetic structure within each species were consistent with the multi-scale results described above when each taxon was evaluated separately, including a clear divergence between the northern and southern samples for both A. germinans and A. schaueriana. Using DAPC, one F₁ interspecific hybrid from AgPRC (Fig. 7A), which was situated between the two primary clusters, was evident despite the individual assignment. Based on two different model-based approaches, we uncovered more evidence that these species are hybridizing and that these hybrids are fertile. Considering the model implemented in the Structure software [38], the most likely k value was 2 based only ΔK (Fig. 6). The differentiation between A. germinans and A. schaueriana remained obvious; however, compared with the DAPC results, there was more evidence supporting ongoing hybridization between these species. Considering the arbitrary threshold of the assignment probability of 0.15, we identified four individuals that were most likely the result of matings between A. germinans and A. schaueriana. When placed between the two primary clusters in the multivariate analysis (Fig. 7A), the same interspecific hybrid individual presented assignment probabilities of 0.566 and 0.434 for each inferred group, which is a reliable indication of an F₁ hybrid (Fig. 7B). Considering each species as a “pure category,” we used another model-based approach to verify the presence of different classes of up to two generation hybrids. As the use of Jeffrey-like and uniform priors yielded slightly different results, with the latter providing more conservative outcomes for the numbers and likelihood of hybrids, we considered only the uniform distribution as prior. The individual inferred as a likely hybrid from PRC considering the Structure and DAPC analyses was unequivocally assigned as an F₁ hybrid with a posterior probability of 1.0. We also observed that two plants from AgALC were likely descendants of a cross between an F₁ individual and an A. germinans genitor (unidirectional backcross—probability > 0.80) (Fig. 7C). No sign of hybridization was evident when considering individuals identified as A. schaueriana, indicating a unidirectional introgression process (Fig. 7 and S5 Fig.).

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Fig 7. Analyses of ongoing hybridization between A. germinans and A. schaueriana.

A) A scatterplot of the first two principal components of the multivariate analysis of DAPC [36]. Each symbol indicates the group to which each individual was assigned. The geographic origin of each individual is denoted for each locality sample such that more than 10% of the total number of individuals is composed of the inferred cluster. A larger symbol indicates that a cluster was predominant in the locality sample (pairwise cluster ratio larger than 1:5), whereas equal symbol sizes indicate similar cluster contributions to the total individuals of each sample. B) Model-based clustering analyses [38,39] considering k = 2, where each individual is represented by a vertical line and each color refers to one cluster; the posterior probability of group membership is indicated. The dashed horizontal lines denote the arbitrary threshold of 0.15, which was used as a sign of possible interspecific hybridization. C) Posterior probability of the model-based approach for identifying species hybrids [45]. Each vertical line also refers to an individual, and different colors indicate distinct classes of individuals: light gray: “pure” A. germinans; dark gray: “pure” A. schaueriana; dark orange: A. germinans second-generation backcrossed individuals; and yellow: F1 interspecific hybrid.

https://doi.org/10.1371/journal.pone.0118710.g007

A. schaueriana microsatellite markers

We characterized the first set of microsatellites for A. schaueriana to complement the molecular markers developed for A. germinans [22–24]. We observed a variable degree of polymorphism among loci and a high transferability rate between these species (Table 2). The present study demonstrates that these markers are valuable molecular tools that can be used to address a wide range of questions regarding these species.

Mating system and intraspecific genetic diversity and structure in A. germinans and A. schaueriana

Considering the progeny array of A. schaueriana, we found an intermediate outcrossing rate, which significantly departed from both 0 and 1, indicating that this population has a mixed mating system [48]. Comparing the t_a values estimated for A. schaueriana from AsAJU (0.529), we observed that this variable closely approximated the t_m estimated via the progeny array (0.542 ± 0.062), indicating that inbreeding is a consistent feature of this population across generations. These results are consistent with the reproductive biology of these species as this tree is self-compatible with a pollinator-dependent generalist pollination system [17], similar to the gray mangrove A. marina [49], which is widespread throughout the IWP region. Considering the three A. germinans progeny arrays from the Pacific coast, we found comparable t_m values (0.583 ± 0.09, 0.774 ± 0.09 and 0.770 ± 0.12 for each array) and proportions of progeny that shared the same male parent for two of the three progeny, indicating that this species may also exhibit moderate levels of self-fertilization. Considering the evaluations of the A. germinans mating system, substantially lower biparental inbreeding was apparent [50]. Unfortunately, these previous analyses are not easily comparable with ours as we used more loci (13) than Nettel et al. [50] (six) and the difference between t_m and t_s is sensitive to the number of loci, with more markers resulting in values closer to the true difference between these parameters [47]. However, using a different method, Cerón-Souza and colleagues [10] suggested that biparental inbreeding may indeed be relevant to the A. germinans mating system, indicating that inbreeding in these species could be affected by both selfing and mating among relatives. Taken together, this evidence suggests that A. germinans, whose flowers are visited by a wide range of insects [18], and A. schaueriana generally exhibit similar mixed mating systems.

For both species throughout the sampling range, we also found evidence of a mixed mating system (average t_a of 0.704 for A. germinans and 0.610 for A. schaueriana) and varying degrees of inbreeding for most of the evaluated samples (Table 3). Previous studies of A. germinans [10,15], A. marina [51–53] and A. bicolor [15] are consistent with these findings. However, we did not observe evidence for large amounts of inbreeding in the southernmost samples of A. germinans or in the southernmost or northernmost samples of A. schaueriana, similar to the findings reported for A. marina [51], which may be due to ecological, geographical and/or historical differences between these species. This mixed mating system involving a broad range of pollinators may represent an adaptation [54] that may be particularly important to mangrove trees as colonizers [1,55] in terms of reproductive assurance [48]. These findings suggest that self-fertilization—and likely mating between relatives—is a frequent feature throughout the genus, and has had substantial influence on the genetic structure of these species due to pollen dispersal restrictions and, consequently, limited gene flow.

The genetic structure patterns we observed for both species support these reproduction-related findings. We argue that this mixed mating system showing biparental inbreeding influences the substantial genetic variation observed among the samples, despite the different global measures of population differentiation. In particular, D was considerably lower for A. schaueriana, which could be explained by its low diversity within populations, likely due to high levels of inbreeding and/or mating between relatives [31]. These summary values are comparable to those previously reported for A. germinans [10,15], A. bicolor [15] and A. marina [52]. Pairwise comparisons between the different population differentiation measurements were significantly correlated for every pair of samples (Fig. 2). This finding indicates that significant genetic differences exist even for geographically close samples despite low values for G_ST and D, which is consistent with multivariate and model-based assignment analyses, which showed very similar results.

Considering the fine-scale genetic structures from the DAPC and Bayesian population assignment methods, with k = 8 for A. germinans, k = 4 for AsN, and k = 6 for AsS, we observed well-defined groups at both the local and regional scales. This was true even where there was no clear physical barrier to pollen and propagule dispersal, for instance, among AsSAL, AsAJU, AsPRM and AsALC or among AgPAa, AgPAb or AgALC, which are samples collected within the world’s largest continuous area of mangrove forests [56] (Figs. 4, 5, S1 and S2 Figs.). AMOVA results also supported this fine-scale genetic structure pattern, as both species had significant fixation index values when the variation among populations within groups was considered (Table 4). For instance, the clear differentiation between AgPAa and AgPAb was striking. These populations are geographically close, within a few kilometers of one another, but are subject to distinct hydrographic regimes [19]. In this case, assuming microsatellites as neutral genetic markers, we argue that tide plays an important role in shaping the genetic diversity of Avicennia. Despite the putative neutrality of these microsatellites, this phenomenon may be enhanced by selective pressures acting on these neutral markers via the hitchhiking effect [57], leading to even more differentiated populations. Thus, hydrographic patterns with a low-frequency tide play an important role as barriers to dispersal, as expected based on the water-based dispersal of mangrove propagules. Only one likely admixed individual was identified within the AgPAa samples, indicating that a limited pollen dispersal constraint also exists, which may be enhanced by the mating systems of these species. In this sense, despite the evidence of LDD for A. germinans [20], our results indicate that regardless of their significant evolutionary consequences [58,59], these phenomena are sufficiently rare that A. germinans and A. schaueriana populations present divergent gene pools even at the local and regional geographic scales.

Therefore, both the present and previous analyses indicates that the pollen and propagule dispersal constraints of the mating system of these species influence their genetic structure at small geographic scales. However, despite the genetic divergence at local and regional spatial scales, a positive relation exists between genetic and geographic distances, leading to an IBD pattern (Fig. 3). Similar to that reported for R. mangle [8,9] and Hibiscus pernambucensis [60], substantial divergence exists between samples from locales north and south of the NEESA for both A. germinans and A. schaueriana. According to the majority of the approaches we used, the most pronounced indications of genetic structure emerged when this divergence was considered. Pairwise G_ST and D values were the highest for pairs of samples between these regions (Fig. 2). The DAPC analyses suggest that the greatest differentiation was found between these northern and southern groups, compared with samples within each cluster (Figs. 4A and 5A). The ΔK values were also the highest for k = 2 for both A. germinans and A. schaueriana (Fig. 6). For A. schaueriana, the amount of variation between these groups was 45.88% according to AMOVA, and lower variation, although significant, was added when we considered more levels of the hierarchy. However, for A. germinans, the between-group fixation indexes were not significant (Table 4), regardless of the mutation model assumed, most likely because AgTMD was the only sample of AgS and because this species exhibits substantial local and regional genetic structure.

As has been previously discussed [8,9,60], the bifurcation of the southern branch of the South Equatorial Current (SEC) into the Brazil Current (BC) and the cross-equatorial North Brazil Current (NBC—northwestward) (Fig. 1–[61]) constrains the movement of propagules between the northern and southern groups. In addition to acting as a barrier, the branching of the SEC, as well as the high velocity of the NBC compared with the BC [61], favor the migration of individuals from the southern to the northern regions, leading to a higher frequency of admixture events in the north. This pattern is readily observed in the Structure software results (Figs. 4, 5, S1 and S2 Figs.). For instance, considering A. germinans, for k = 2, the absence of admixed individuals in the TMD sample and their presence in the AgPRC samples follow the direction of the NBC marine current. A. schaueriana exhibits the same pattern: for k = 2, there is little evidence of admixture in the southern group, whereas substantial evidence of admixed individuals exists in AsALC and AsPRC samples. Moreover, regarding AsN, there are indications that propagule flow follows the direction of the NBC. In contrast, AsS shows a more complex pattern in which no single direction of admixed individuals is apparent for k = 2 or 6 (Fig. 5B). This result may be related to the slower mean velocity of the BC and its seasonal variations in velocity and direction [61] in southern and southeastern Brazil, where AsGPM, AsUBA and AsCNN were sampled. Furthermore, not only the direction but also the speed and seasonal variance of the marine currents play an important role in the genetic diversity of these sea-dispersed plants at multiple geographic scales. However, the role of marine currents in shaping mangrove genetic diversity is not restricted to the Atlantic coast of South America. Along the northwestern coast of Mexico, for instance, the California Current and the El Niño Southern Oscillation could explain the patterns of gene flow observed for R. mangle [62]. Regarding the IWP biogeographic region, links between marine currents and genetic variation have been reported for several different mangrove taxa, including R. mucronata Lam. (Rhizophoraceae) [63], Ceriops tagal (Perr.) (Rhizophoraceae) [64] Kandelia candel (L.) Druce (Rhizophoraceae) [65] and Lumnitzera racemosa Willd (Combretaceae) [66]. Considered together with our findings, this body of evidence suggests that the influence of surface marine currents on genetic variation in mangroves, and likely other sea-dispersed organisms, is a general feature of evolution.

Ongoing hybridization between A. germinans and A. schaueriana

There is evidence of an ancient introgression between A. germinans and A. bicolor, a species with a limited distribution along the Pacific coast of Central America [1], as well as chloroplast capture between A. germinans and A. schaueriana in the Atlantic basin [15]. Although we were unable to evaluate any chloroplast genome markers, we found evidence that ongoing hybridization is indeed occurring between these species within the A. germinans and A. schaueriana sympatry zone. To the best of our knowledge, this is the first report of ongoing hybridization in Avicennia.

These mangrove species present distinct gene pools, which is evident when these species are compared using the pairwise G_ST and D values between samples or using the DAPC approach, in which the genetic diversity between each species is much greater than the variation within each species (Figs. 2 and 7). Moreover this is consistent with the AMOVA at the interspecific level of the hierarchy (Table 4). In addition to differentiating these two species, these analyses also recapitulate the previously discussed genetic structure within each species. The multivariate assignment approach suggests a likely interspecific hybrid identified as A. germinans from AgPRC, which is graphically located between the clusters of individuals representing each species (Fig. 7A). Further Bayesian evaluations not only corroborated the likely hybrid identified using DAPC as an F₁ hybrid but also assigned other A. germinans individuals from AgALC as likely second-generation backcrosses between F₁ hybrids and this species (Fig. 7C); these results also indicate that eventual hybrids are fertile, at least when mating with A. germinans. The Bayesian methods also revealed that this introgression is likely unidirectional as only individuals identified as A. germinans showed evidence of ongoing admixture between the species (as illustrated in S5 Fig.). These species share both pollinators [17,18] and flower traits [1,17], and a reproductive phenological overlap has been reported [19], indicating that hybridization is possible between these species. Additionally, during our sampling, A. germinans was more commonly found in Alcântara, Maranhão, Brazil [19], but was much less abundant in Paracuru, Ceará, throughout our sampling. These findings indicate that post-zygotic mechanisms are related to this asymmetric hybridization, as was previously observed for other mangrove genera [12,67]. We consider the mechanisms that generate and maintain this unidirectional introgression worthy of further investigation.

The ancient introgression between A. bicolor and A. germinans observed along the Pacific coast of Central America [15] was related to the higher diversity in that region than the Atlantic coast [10,15]. However, when considering the South American Atlantic coast, this association is not possible as AgAJU and AgPRC do not show higher genetic diversities in terms of the number of alleles or expected heterozygosity than locales with no evidence of hybridization (Table 3). Therefore, we argue that ongoing interspecific hybridization did not increase the genetic diversity of A. germinans in the samples we evaluated. This could indicate that the observed interspecific mating was recent and that too little time has passed for A. schaueriana alleles to spread among the A. germinans populations or, alternatively, that natural selection is acting against the hybrid, reducing the spread of its alleles. Again, although we may hypothesize about the consequences of the observed hybridization, we encourage further investigations into the effects of interspecific hybridization on not only the genetic diversity of populations but also individual phenotype and fitness.

Concluding remarks

Using the first set of microsatellites developed for A. schaueriana as well as markers previously developed for A. germinans, we studied three biological aspects of these species: the existence of hybridization between these species, their mating systems, and the organization of neutral genetic variants at different geographic scales. Our results suggest that an interplay between intrinsic (e.g., mating system, limited pollen and propagule dispersal but not hybridization) and extrinsic factors (e.g., marine currents and tide) shape the genetic diversity of A. germinans and A. schaueriana, leading to genetic diversity structured at the micro-, meso- and macro-scales for both of these Avicennia species.

Similar patterns of neutral genetic variation organization have been observed in different taxa of mangrove species, which is likely related to their shared colonization ability [1,55]. For instance, a large-scale genetic structure was reported for Rhizophora mangle [8,9]; however, its genetic diversity is also locally and regionally organized on smaller scales [10]. This multiple-scale genetic structure is observed in these phylogenetically distant species regardless of the different propagule features of each genus [5,6]. The generality or specificity of these findings and the mechanisms that generate these similar patterns remains to be evaluated in other mangrove species, perhaps using a landscape genetics approach [68]. However, this investigation demonstrates a consistent, multiple-geographic-scale genetic structure pattern for two Neotropical Avicennia species. Moreover, we are aware that these different spatial scales imply distinct temporal scales of evolutionary response. Considering this, future efforts will be focused on elucidating the processes that generate and maintain these patterns.